DatriseAI-first ETL

Particle to MySQL Integration

AI-first ETL from Particle into MySQL. Governed entities, incremental sync, typed landing tables.

How Datrise loads Particle into MySQL

Datrise syncs Particle's devices, events, variables, firmware versions, product fleets, and device logs into MySQL as a typed table per source entity. Flexible or custom fields land in JSON columns, and timestamps such as created, updated, and status changes are typed as DATETIME/TIMESTAMP.

Sync is incremental: Datrise uses a watermark on updated-at, applied with INSERT … ON DUPLICATE KEY UPDATE, so re-runs update only what changed. Optional RANGE partitioning by load date. MySQL collation matters for CRM text, so Datrise lands utf8mb4 to preserve emoji and non-Latin characters.

Ideal for operational reporting and app databases already standardized on MySQL.

Endpoints

Particle: IoT device fleet telemetry and events.

MySQL: Widely used OSS relational engine (InnoDB).

How Particle entities map to MySQL

Particle entityMySQL objectNotes
devicesparticle_devicesid PK · custom fields → JSON columns
eventsparticle_eventsDATETIME/TIMESTAMP events
variablesparticle_variablesid PK · linked to particle_devices
firmware versionsparticle_firmware_versionsid PK · linked to particle_devices

FAQ

How does Datrise handle Particle's custom fields in MySQL?

Flexible values are stored as JSON columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native MySQL types.

How does the Particle to MySQL sync stay up to date?

It runs incrementally — Datrise uses a watermark on updated-at, applied with INSERT … ON DUPLICATE KEY UPDATE.

Related pipelines

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